Evidence map›Paper›PMID 42516921›Full record

ArticleDigital health

Generative AI versus human conversational agent for reducing procrastination: A randomized pilot trial.

Severin Hennemann, Julia M Fähnrich, Cornelius Tietze, Michael Witthöft, Stefanie M Jungmann

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Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Severin HennemannDepartment of Clinical Psychology, Psychotherapy and Experimental Psychopathology, University of Mainz, Mainz, Germany.ORCID https://orcid.org/0000-0001-8780-9985
Julia M FähnrichDepartment of Clinical Psychology, Psychotherapy and Experimental Psychopathology, University of Mainz, Mainz, Germany.
Cornelius TietzeDepartment of Clinical Psychology, Psychotherapy and Experimental Psychopathology, University of Mainz, Mainz, Germany.
Michael WitthöftDepartment of Clinical Psychology and Psychotherapy, Ruhr-University of Bochum, Bochum, Germany.
Stefanie M JungmannDepartment of Clinical Psychology and Psychotherapy of Childhood and Adolescence, University of Mainz, Mainz, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The use of generative artificial intelligence (AI) based chatbots in mental health interventions is rapidly evolving, but evidence of their efficacy and safety is scarce. This randomized pilot trial investigated the feasibility, efficacy, mechanisms, and unwanted effects of a generative AI chatbot (ChatGPT-4) vs. human conversational agent as a cognitive behavioral micro-intervention for procrastination. Methods: 62 university students (M Results: Intention-to-treat analyses revealed a non-significant group × time interaction effect ( Conclusions: Our findings do not indicate superiority of either conversational agent and both interventions had comparable, rather high rates of unwanted effects, indicating that more research in larger, clinically meaningful samples is needed to confirm the efficacy and safety of AI-based (micro-)interventions.

Indexed as

artificial intelligencechatbotchatGPTlarge language modelprocrastination

Identifiers

PMID42516921
PMCPMC13402774

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.